Paper
8 February 2015 Autonomous detection of text fade point with color laser printers
Yanling Ju, Eric Maggard, Renee Jessome, Jan Allebach
Author Affiliations +
Proceedings Volume 9396, Image Quality and System Performance XII; 93960G (2015) https://doi.org/10.1117/12.2081238
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
Fading is one of the issues of most critical concern for print quality degradation with color laser electro- photographic printers. Fading occurs when the cartridge is depleted. ISO/IEC 19798:2007(E) specifies a process for determining the cartridge page yield for a given color electro-photographic printer model. It is based on repeatedly printing a suite of test pages, followed by visual examination of the sequence of printed diagnostic pages. But this method is a very costly process since it involves visual examination of a large number of pages. And also the final decision is based on the visual examination of a specially designed diagnostic page, which is different than typical office document pages, since it consists of color bars, and contains no text. In this paper, we propose a new method to autonomously detect the text fading in prints from home or office color printers using a typical office document page instead of a specially designed diagnostic page. In our method, we scan and analyze the printed pages to predict where expert observers would judge fading to have occurred in the print sequence. Our approach is based on a machine-learning framework in which features derived from image analysis are mapped to a fade point prediction.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanling Ju, Eric Maggard, Renee Jessome, and Jan Allebach "Autonomous detection of text fade point with color laser printers", Proc. SPIE 9396, Image Quality and System Performance XII, 93960G (8 February 2015); https://doi.org/10.1117/12.2081238
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Cited by 1 scholarly publication.
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KEYWORDS
Diagnostics

Printing

Binary data

Nonimpact printing

Visualization

Image analysis

Image quality

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